Person:
Malanda Trigueros, Armando

Profile Picture

Email Address

person.page.identifierURI

https://academica-e.unavarra.es/handle/2454/49489

Birth Date

Research Projects

Organizational Units

Job Title

Last Name

Malanda Trigueros

First Name

Armando

person.page.departamento

Ingeniería Eléctrica, Electrónica y de Comunicación

person.page.instituteName

ISC. Institute of Smart Cities

ORCID

0000-0002-3122-9049

person.page.upna

379

Name

Filters

2009 - 200912020 - 20221
Reset filters

Settings

Author: Rodríguez Carreño, Ignacio × Subject: Neuromuscular disorders ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    PublicationOpen Access
    Métodos de procesamiento y análisis de señales electromiográficas
    (Gobierno de Navarra, 2009) Gila Useros, Luis; Malanda Trigueros, Armando; Rodríguez Carreño, Ignacio; Rodríguez Falces, Javier; Navallas Irujo, Javier; Ingeniería Eléctrica y Electrónica; Ingeniaritza Elektrikoa eta Elektronikoa
    La electromiografía clínica es una metodología de registro y análisis de la actividad bioeléctrica del músculo esquelético orientada al diagnóstico de las enfermedades neuromusculares. Las posibilidades de aplicación y el rendimiento diagnóstico de la electromiografía han evolucionado paralelamente al conocimiento de las propiedades de la energía eléctrica y al desarrollo de la tecnología eléctrica y electrónica. A mediados del siglo XX se introdujo el primer equipo comercial de electromiografía para uso médico basado en circuitos electrónicos analógicos. El desarrollo posterior de la tecnología digital ha permitido disponer de sistemas controlados por microprocesadores cada vez más fiables y potentes para captar, representar, almacenar, analizar y clasificar las señales mioeléctricas. Es esperable que el avance de las nuevas tecnologías de la información y la comunicación pueda conducir en un futuro próximo a la aplicación de desarrollos de inteligencia artificial que faciliten la clasificación automática de señales así como sistemas expertos de apoyo al diagnóstico electromiográfico.
  • Thumbnail Image
    PublicationOpen Access
    Automatic jitter measurement in needle-detected motor unit potential trains
    (Elsevier, 2022) Malanda Trigueros, Armando; Stashuk, Daniel W.; Navallas Irujo, Javier; Rodríguez Falces, Javier; Rodríguez Carreño, Ignacio; Valle, César; Garnés Camarena, Óscar; Ingeniería Eléctrica, Electrónica y de Comunicación; Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
    In an active motor unit (MU), the time intervals between the firings of its muscle fibers vary across successive MU activations. This variability is called jitter and is increased in pathological processes that affect the neuromuscular junctions or terminal axonal segments of MUs. Traditionally, jitter has been measured using single fiber electrodes (SFEs) and a difficult and subjective manual technique. SFEs are expensive and reused, implying a potential risk of patient infection; so, they are being gradually substituted by safer, disposable, concentric needle electrodes (CNEs). As CNEs are larger, voltage contributions from individual fibers of a MU are more difficult to detect, making jitter measurement more difficult. This paper presents an automatic method to estimate jitter from trains of motor unit potentials (MUPs), for both SFE and CNE records. For a MUP train, segments of MUPs generated by single muscle fibers (SF MUP segments) are found and jitter is measured between pairs of these segments. Segments whose estimated jitter values are not reliable, according to several SF MUP segment characteristics, are excluded. The method has been tested in several simulation studies that use mathematical models of muscle fiber potentials. The results are very satisfactory in terms of jitter estimation error (less than 10% in most of the cases studied) and mean number of valid jitter estimates obtained per simulated train (greater than 1.0 in many of the cases and less than 0.5 only in the most complicated). A preliminary study with real signals was also performed, using 19 MUP trains from 3 neuropathic patients. Jitter measurements obtained by the automatic method were compared with those extracted from a commercial system (Keypoint) and the edition and supervision of an expert electromyographer. From these measurements 63% were taken from equivalent interval pair sites within the time span of the MUP trains and, as such, were considered as compatible measurements. Differences in jitter of these compatible measurements were very low (mean value of 1.3 μs, mean of absolute differences of 2.97 μs, 25% and 75% percentile intervals of − 0.85 and 3.82 μs, respectively). Although new tests with larger number of real recordings are still required, the method seems promising for clinical practice.